| Bottom-up abstractive summarization S Gehrmann, Y Deng, AM Rush Proceedings of the 2018 Conference on Empirical Methods in Natural Language …, 2018 | 307 | 2018 |
| LSTMVis: A tool for visual analysis of hidden state dynamics in recurrent neural networks H Strobelt*, S Gehrmann*, H Pfister, AM Rush IEEE transactions on visualization and computer graphics 24 (1), 667-676, 2017 | 277* | 2017 |
| Comparing deep learning and concept extraction based methods for patient phenotyping from clinical narratives S Gehrmann, F Dernoncourt, Y Li, ET Carlson, JT Wu, J Welt, J Foote Jr, ... PloS one 13 (2), e0192360, 2018 | 117* | 2018 |
| Seq2Seq-Vis: A visual debugging tool for sequence-to-sequence models H Strobelt*, S Gehrmann*, M Behrisch, A Perer, H Pfister, AM Rush IEEE transactions on visualization and computer graphics 25 (1), 353-363, 2018 | 99 | 2018 |
| GLTR: Statistical Detection and Visualization of Generated Text S Gehrmann, H Strobelt, AM Rush ACL Demo 2019, 2019 | 55 | 2019 |
| End-to-End Content and Plan Selection for Data-to-Text Generation S Gehrmann, FZ Dai, H Elder, AM Rush INLG 2018, 2018 | 38 | 2018 |
| exBERT: A visual analysis tool to explore learned representations in transformers models B Hoover, H Strobelt, S Gehrmann ACL Demo 2020, 2019 | 27 | 2019 |
| ToTTo: A controlled table-to-text generation dataset AP Parikh, X Wang, S Gehrmann, M Faruqui, B Dhingra, D Yang, D Das EMNLP 2020, 2020 | 26 | 2020 |
| LSTM Networks Can Perform Dynamic Counting M Suzgun, S Gehrmann, Y Belinkov, SM Shieber Deep Learning and Formal Languages Workshop at ACL 19, 2019 | 23 | 2019 |
| Behind the scenes: A medical natural language processing project JT Wu, F Dernoncourt, S Gehrmann, PD Tyler, ET Moseley, ET Carlson, ... International journal of medical informatics 112, 68-73, 2018 | 21 | 2018 |
| Encoder-agnostic adaptation for conditional language generation ZM Ziegler*, L Melas-Kyriazi*, S Gehrmann, AM Rush arXiv preprint arXiv:1908.06938, 2019 | 19 | 2019 |
| Visual Interaction with Deep Learning Models through Collaborative Semantic Inference S Gehrmann*, H Strobelt*, R Krüger, H Pfister, AM Rush VAST 2019, 2019 | 17 | 2019 |
| Investigating gender bias in language models using causal mediation analysis J Vig, S Gehrmann, Y Belinkov, S Qian, D Nevo, Y Singer, S Shieber Advances in Neural Information Processing Systems 33, 2020 | 14* | 2020 |
| E2E NLG Challenge Submission: Towards Controllable Generation of Diverse Natural Language H Elder, S Gehrmann, A O’Connor, Q Liu INLG 2018, 0 | 11* | |
| Deploying AI methods to support collaborative writing: a preliminary investigation S Gehrmann*, L Urke*, O Amir, BJ Grosz Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human …, 2015 | 9 | 2015 |
| The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models I Tenney*, J Wexler*, J Bastings, T Bolukbasi, A Coenen, S Gehrmann, ... EMNLP Demo 2020, 2020 | 8 | 2020 |
| Memory-augmented recurrent neural networks can learn generalized Dyck languages M Suzgun, S Gehrmann, Y Belinkov, SM Shieber arXiv preprint arXiv:1911.03329, 2019 | 7 | 2019 |
| Accelerating antimicrobial discovery with controllable deep generative models and molecular dynamics P Das, T Sercu, K Wadhawan, I Padhi, S Gehrmann, F Cipcigan, ... nature BME, 2020 | 4 | 2020 |
| Interpretability and analysis in neural NLP Y Belinkov, S Gehrmann, E Pavlick Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 3 | 2020 |
| Performance under pressure in skill tasks: An analysis of professional darts M Ötting, C Deutscher, S Schneemann, R Langrock, S Gehrmann, ... PloS one 15 (2), e0228870, 2020 | 3 | 2020 |
Alexander M. RushAssociate Professor, Cornell UniversityVerified email at seas.harvard.edu
